Manufacturing AI checklist

Verify an AI-assisted manufacturing RFQ summary against the source packet.

Inventory every supplied and referenced file, define a fixed extraction structure, verify each material statement, preserve unknowns, and keep commercial, technical, and quality decisions with authorized people.

Start with the checklist

Purpose

Use AI to organize the review—not to accept the work.

A manufacturing request for quote can move customer demand, technical requirements, quality expectations, delivery requests, and commercial terms into the company at once. An AI-assisted summary may make the packet easier to navigate, but speed is useful only when missing information, conflicting revisions, source identity, and uncertainty remain visible.

Apply this checklist before an extraction or summary enters estimating or contract review. First confirm that the selected tool and information are approved by the responsible company owners. Then treat the generated output as a proposed work product that an estimator, contract-review owner, engineer, quality representative, or other authorized role must challenge against the original material.

Step 1 · Packet inventory

List what arrived, what is referenced, and what is missing.

Build the inventory before asking for a summary. The inventory gives the reviewer a denominator: the generated output can be checked against a known set of supplied files and unresolved references instead of being judged only by how complete it sounds.

List every received email, drawing, model, specification, quality clause, quantity, due date, and commercial attachment.
Record each filename, document identifier, revision, and date exactly as displayed; do not normalize away a meaningful difference.
List every document, specification, or clause referenced by another file but not supplied in the packet.
Keep superseded, marked-up, translated, or convenience copies visibly separate from the candidate controlling source.
Record unreadable, password-protected, incomplete, duplicated, or unsupported files as review conditions rather than silently omitting them.

Step 2 · Extraction structure

Define the requested fields and the treatment of unknowns.

Ask the tool to organize supplied facts into a fixed structure. Require a source pointer for material fields and an explicit unknown when the packet does not support an answer. Do not ask the tool to infer a missing specification, choose an older revision, resolve contradictory requirements, or invent a delivery date.

Suggested manufacturing RFQ extraction structure
Field group	Record from the supplied packet	Keep visible for review
Request	Customer, request identifier, contact context, response date, and requested delivery.	Ambiguous dates, conflicting messages, and missing request identifiers.
Item	Part or assembly identifier, quantity, drawing, revision, model, and configuration references.	Revision conflicts, missing models, and uncertain applicability.
Requirements	Referenced specifications, clauses, material, special processes, inspection, testing, first-article, and certification requests.	Missing referenced documents, unverified interpretations, and owner questions.
Packet state	Files supplied, duplicates, convenience copies, unreadable items, and references not received.	The gap between the packet inventory and the generated extraction.
Review routing	Open question, proposed owner role, source location, verification state, and reviewer disposition.	Questions that have not yet reached the person authorized to answer them.

Step 3 · Source verification

Open the source for every material statement.

If the tool cannot point the reviewer to an adequate source, the statement is not ready to guide a quote. A reviewer may still investigate the issue through the company’s normal process, but the generated language itself does not close the gap.

Open the cited source and confirm that it is one of the inventoried files.
Check the exact statement, value, unit, identifier, date, and revision against the source.
Determine whether the extraction copied a fact, summarized language, or introduced an unsupported inference.
Compare the completed extraction with the original packet inventory so an entire file or attachment cannot disappear unnoticed.
Keep conflicts, unreadable content, missing references, and unresolved applicability questions visible.
Mark the verification result and responsible reviewer; do not convert an unverified field into a confident statement.

Step 4 · Reserved decisions

Separate packet organization from company commitments.

Decisions that remain outside the AI extraction
Reserved decision	AI-assisted work may support	Authority remains with
Bid or no bid	Organized facts, deadlines, missing inputs, and open questions.	The designated commercial or business owner.
Technical feasibility	Cited requirements, comparison, and a visible question list.	Qualified engineering and process owners.
Process and supplier approach	Candidate requirement categories and supplied constraints.	Authorized manufacturing, supply-chain, engineering, and quality roles.
Price, margin, capacity, and delivery	Structured quantities, requested dates, and assumptions awaiting confirmation.	Commercial, operations, finance, and other assigned decision owners.
Contractual acceptance	A source-linked review package and unresolved-term list.	The functions authorized by the company to review and accept terms.
Quality or engineering disposition	Evidence organization and exception routing.	The qualified person acting within actual delegated authority.

Step 5 · Reviewable artifact

Save the evidence needed to challenge and continue the work.

The useful output is not a polished paragraph alone. Save a packet register that preserves the review state and can move through the company’s existing process without hiding how the summary was produced. The appropriate owner must determine storage, access, retention, approval, and signature requirements for the actual workflow.

Packet inventory with exact source identifiers and revision information.
Extracted facts with citations or precise source locations.
Missing documents, contradictions, unreadable content, assumptions, and unsupported inferences.
Open questions and the role expected to answer each one.
Reviewer identity, review date, corrections, and disposition for material fields.
The resulting handoff, escalation, or stop decision without implying that the AI made it.

Synthetic example

Keep a missing material specification visible.

Imagine the fictional manufacturer Elm River Precision receives drawing ER-4412 Revision C. The drawing references material specification ER-MAT-88, but that specification is absent from the supplied packet. The inventory records the drawing and the missing referenced specification separately. The extraction identifies the material reference, cites the drawing location, marks the underlying specification as not supplied, and routes a clarification question to the appropriate owner.

A safe summary does not silently reuse a specification from an older job, select a previous revision, declare technical feasibility, or promise delivery. The example demonstrates source preservation and escalation only; it is not evidence of a customer result, an aerospace-specific approval process, or compliance with a contract, quality system, or regulation.

Sources and next action

Practice on synthetic or explicitly approved information.

The checklist adapts the Academy’s source-verification practice to a public operating aid. The Connecticut Manufacturing Report provides state-level context on reported uses of AI for document development, research, data analysis, and process automation. IAQG’s public supply-chain guidance provides broader planning and contract-review context. Neither source approves a particular tool, packet, interpretation, or company workflow.

Apply the checklist to a synthetic packet or information explicitly approved for the selected tool and exercise.
Ask an estimator or contract-review owner to challenge the packet inventory, extraction, citations, gaps, and reserved decisions.
Record corrections and decide whether the workflow should advance, narrow, prepare further, or stop.
Use the free Academy learning path for guided synthetic practice before applying the method to company work.

2026 Connecticut Manufacturing Report IAQG planning and contract-review guidance

Practice, then inspect proof

Learn the method safely before applying it to company work.

The free Academy uses synthetic manufacturing material. The Qualification Compiler case study shows how the same source, gap, and human-authority principles appear in a bounded demonstration.

Explore the free Academy Review the Qualification Compiler case study